To better quantify morphologic tumor activity (MTA), as determined by nuclear morphology, image analysis was performed.
The prognosis of patients with breast ductal carcinoma in situ (DCIS) to develop invasive carcinoma can be improved by adding quantitative nuclear features obtained by image analysis to clinical factors and histopathological grades.
We utilize the same DCIS patient cohort and clinical and pathologic factors as in the previous study by Miller, et al. [ 12] to provide an estimate of additional benefit from considering quantitative nuclear features determined by image analysis.
Following analysis with immunofluorescence microscopy, the images were scored for distribution of nuclear size by computer-assisted image analysis (AxioVision software 4).
This result was confirmed by quantifying the extent of nuclear accumulation through image analysis (see Figure 1C), whereby the nuclear to cytoplasmic ratio (Fn/c) was determined as described previously [ 29, 30].
The nuclear DNA content was quantified by image analysis with the software CIRES (Cell Image Retrieval and Evaluation System-Kontron Eletronik) installed in Axioskop microscope (Zeiss).
This result was further confirmed by counting neuron-specific nuclear protein-positive cells within the GCL in flat-mounted retinas by confocal image analysis at 7 days and 14 days after ischemic injury.
Traditionally, these measurements require labeling and imaging, and then nuclear measurement using image analysis.
To detect individual cells in tissue sections, a nuclear cell quantification image analysis algorithm (IHC Nuclear Quantification, Aperio) was trained on control slides by defining the color vectors for the hematoxylin nuclear counterstain and primary positive chromagen DAB, minimum and maximum size for nuclei, and threshold ranges for intensity of nuclear staining.
